Innovative Time and Attendance System Software Selection for a Private Hospital: Leveraging the Entropy-TOPSIS Method

Innovative Time and Attendance System Software Selection for a Private Hospital: Leveraging the Entropy-TOPSIS Method


  • Norazean Nordin College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, Seremban, Negeri Sembilan
  • Eaisya Nurfarhana Samat College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, Seremban, Negeri Sembilan
  • Fairuz Noraainaa Adam College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, Seremban, Negeri Sembilan
  • Nor Faradilah Mahad College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, Seremban, Negeri Sembilan



MCDM, Entropy, TOPSIS, Time and Attendance System


Automated time and attendance systems offer the capability to track employee attendance, calculate working days, overtime hours, and late arrivals, and generate comprehensive attendance reports, thereby improving workforce productivity. Investing in suitable time and attendance system software is crucial for a company since many businesses are adopting digital time and attendance systems that automatically collect and analyse data to increase productivity and efficiency. This decision-making process considers numerous contradictory criteria. Thus, for this study, the Multi-Criteria Decision Making (MCDM) methods, namely Entropy and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), were used to choose the best time and attendance system software for a private hospital. There were six (6) criteria used to evaluate the time and attendance system software. The criteria were categorised as cost  ease of use  being compatible with existing HR software and operating system  reporting capabilities  customer service  and scheduling capabilities  Meanwhile, the alternatives are labelled as  The outcomes showed that the ranking order for the criteria is  while the ranking order for the alternative is  respectively. In conclusion, the Entropy-TOPSIS can be used to assess and rank the alternatives.


Download data is not yet available.


Abdullah, L., & Otheman, A. (2013). A new entropy weight for sub-criteria in interval Type-2 Fuzzy TOPSIS and its application. International Journal of Intelligent Systems and Applications, 5(2), 25–33.

Adewole, K. S., Abdulsalam, S. O., Babatunde, R. S., Shittu, T. M., & Oloyede, M. O. (2014). Development of fingerprint biometric attendance system for non-academic staff in a tertiary institution. Computer Engineering and Intelligent Systems, 5(2), 62–70.

Alamri, F. S., Saeed, M. H., & Saeed, M. (2024). A hybrid entropy-based economic evaluation of hydrogen generation techniques using Multi-Criteria Decision Making. International Journal of Hydrogen Energy, 49, 711-723.

Alonso, J. A., & Lamata, M. T. (2006). Consistency in the analytic hierarchy process: a new approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 14(4), 445–459.

Chen, C.-T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114, 1–9.

Dwivedi, P. P., & Sharma, D. K. (2023). Evaluation and ranking of battery electric vehicles by Shannon’s entropy and TOPSIS methods. Mathematics and Computers in Simulation, 212, 457–474.

Ebrahim, M. A., Bader, J., & Sankar, J. P. (2019). Attendance management and employee performance among selected commercial banks in the Kingdom of Bahrain. International Journal of Economics, Commerce and Management United Kingdom, VII(12), 761–762.

Elsayed, A. K., Dawood, A. S., & Karthikeyan, R. (2017). Evaluating alternatives through the application of TOPSIS method with entropy weight. International Journal of Engineering Trends and Technology, 46, 60–66.

Fajdek-Bieda, A. (2021). Using Entropy-VIKOR method in chemical processes optimization. Procedia Computer Science, 192, 4208–4217.

Goswami, S. S., & Behera, D. K. (2020). Implementation of ENTROPY-ARAS decision making methodology in the selection of best engineering materials. Materials Today: Proceedings, 38, 2256–2262.

Goswami, S. S., Jena, S., & Behera, D. K. (2022). Selecting the best AISI steel grades and their proper heat treatment process by integrated entropy-TOPSIS decision making techniques. Materials Today: Proceedings, 60, 1130–1139.

Hafezalkotob, A., & Hafezalkotob, A. (2015). Extended MULTIMOORA method based on Shannon entropy weight for materials selection. Journal of Industrial Engineering International, 12(1), 1–13.

Haq, R. S. U., Saeed, M., Mateen, N., Siddiqui, F., & Ahmed, S. (2023). An interval-valued neutrosophic based MAIRCA method for sustainable material selection. Engineering Applications of Artificial Intelligence, 123, 106177.

Huang, J. (2008). Combining entropy weight and TOPSIS method for information system selection. 2008 IEEE Conference on Cybernetics and Intelligent Systems (pp. 1281–1284).

Hwang, C.-L., & Yoon, K. (1981). Methods for Multiple Attribute Decision Making. In Multiple Attribute Decision Making: Methods and Applications A State-of-the-Art Survey (pp. 58–191). Springer Berlin Heidelberg.

Jahanshahloo, G. R., Lotfi, F. H., & Izadikhah, M. (2006). Extension of the TOPSIS method for decision-making problems with fuzzy data. Applied Mathematics and Computation, 181(2), 1544–1551.

Kumar, R., Singh, S., Bilga, P. S., Singh, J., Singh, S., Scutaru, M. L., & Pruncu, C. I. (2021). Revealing the benefits of entropy weights method for multi-objective optimization in machining operations: A critical review. Journal of materials research and technology, 10, 1471-1492.

Lan, L. T. H., Hien, D. T. T., Thong, N. T., Smarandache, F., & Giang, N. L. (2023). An ANP-TOPSIS model for tourist destination choice problems under Temporal Neutrosophic environment [Formula presented]. Applied Soft Computing, 136.

Li, X., Wang, K., Liuz, L., Xin, J., Yang, H., & Gao, C. (2011). Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering, 26, 2085–2091.

Luo, L., Zhang, C., & Liao, H. (2019). Distance-based intuitionistic multiplicative MULTIMOORA method integrating a novel weight-determining method for multiple criteria group decision making. Computers and Industrial Engineering, 131, 82–98.

Olagunju, M., Adeniyi, A. E., & Oladele, T. O. (2018). Staff attendance monitoring system using fingerprint biometrics general terms. International Journal of Computer Applications, 179(21), 975–8887.

Oloyede, M. O., Adedoyin, A. O., & Adewole, K. S. (2013). Fingerprint biometric authentication for enhancing staff attendance system. International Journal of Applied Information Systems, 5(3), 19–24.

Oo, S. B., Oo, N. H. M., Chainan, S., Thongniam, A., & Chongdarakul, W. (2018). Cloud-based Web application with NFC for employee attendance management system. 2018 International Conference on Digital Arts, Media and Technology (ICDAMT) (162–167).

Rajak, M., & Shaw, K. (2019). Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS. Technology in Society, 59, 101186.

Ramezani, M., Bashiri, M., & Atkinson, A. C. (2011). A goal programming-TOPSIS approach to multiple response optimization using the concepts of non-dominated solutions and prediction intervals. Expert Systems with Applications, 38(8), 9557–9563.

Roszkowska, E. (2013). Rank ordering criteria weighting methods – A comparative overview. Optimum. Studia Ekonomiczne, 5(65), 14–33.

Saaty, R. W. (1987). The analytic hierarchy process-what it is and how it is used. Mathematical Modelling, 9(5), 161–176.

Shannon, C. E. (1948). A Mathematical theory of communication. The Bell System Technical Journal, 27, 623–656.

Shih, H. S., Shyur, H. J., & Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7–8), 801–813.

Srdjevic, B., Medeiros, Y. D. P., & Faria, A. S. (2004). An objective multi-criteria evaluation of water management scenarios. Water Resources Management, 18, 35–54.

Thakkar, J. J. (2021). Technique for Order Preference and Similarity to Ideal Solution (TOPSIS). In Multi-Criteria Decision Making (pp. 83–91). Springer Singapore.

Triantaphyllou, E., & Lin, C.-T. (1996). Development and Evaluation of Five Fuzzy Multiattribute Decision-Making Methods.

Tuş, A., & Adalı, E. A. (2019). The new combination with CRITIC and WASPAS methods for the time and attendance software selection problem. OPSEARCH, 56(2), 528–538.

Tyagi, M. (2019). Effect of HR interventions based on Biometric Attendance System records to improve Employee Absenteeism. Journal of the Academy of Hospital Administration, 31(2), 5–13.

Tzeng, G. H., Chen, T. Y., & Wang, J. C. (1998). A weight-assessing method with habitual domains. European Journal of Operational Research, 110(2), 342–367.

Wang, T. C., & Chang, T. H. (2007). Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Systems with Applications, 33(4), 870–880.

Wang, Y. J., & Lee, H. S. (2007). Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Computers and Mathematics with Applications, 53(11), 1762–1772.

Yadav, A. K., Singh, K., Srivastava, P. K., & Pandey, P. S. (2023). I-MEREC-T: Improved MEREC-TOPSIS scheme for optimal network selection in 5G heterogeneous network for IoT. Internet of Things, 22, 100748.

Zardari, N. H., Ahmed, K., Shirazi, S. M., & Yusop, Z. Bin. (2015). Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management. Springer International Publishing.

Zeleny, M. (2012). Multiple Criteria Decision Making Kyoto 1975. Springer Science & Business Media.

Zhang, Y., Zhang, Y., Zhang, H., & Zhang, Y. (2022). Evaluation on new first-tier smart cities in China based on entropy method and TOPSIS. Ecological Indicators, 145, 109616.




How to Cite

Nordin, N., Samat, E. N., Adam, F. N., & Mahad, N. F. (2024). Innovative Time and Attendance System Software Selection for a Private Hospital: Leveraging the Entropy-TOPSIS Method. Journal of Computing Research and Innovation, 9(1), 79–90.



General Computing

Most read articles by the same author(s)